Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations1048532
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory917.8 MiB
Average record size in memory917.8 B

Variable types

Categorical5
Text9
DateTime1
Numeric1

Alerts

Application Number has unique values Unique

Reproduction

Analysis started2025-03-26 02:30:46.919648
Analysis finished2025-03-26 02:31:17.275994
Duration30.36 seconds
Software versionydata-profiling vv4.15.1
Download configurationconfig.json

Variables

Gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.9 MiB
Male
575916 
Female
462128 
Other
 
10488

Length

Max length6
Median length4
Mean length4.8914788
Min length4

Characters and Unicode

Total characters5128872
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowMale
4th rowMale
5th rowMale

Common Values

ValueCountFrequency (%)
Male 575916
54.9%
Female 462128
44.1%
Other 10488
 
1.0%

Length

2025-03-26T08:01:17.367655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T08:01:17.450745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
male 575916
54.9%
female 462128
44.1%
other 10488
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e 1510660
29.5%
a 1038044
20.2%
l 1038044
20.2%
M 575916
 
11.2%
F 462128
 
9.0%
m 462128
 
9.0%
O 10488
 
0.2%
t 10488
 
0.2%
h 10488
 
0.2%
r 10488
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5128872
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1510660
29.5%
a 1038044
20.2%
l 1038044
20.2%
M 575916
 
11.2%
F 462128
 
9.0%
m 462128
 
9.0%
O 10488
 
0.2%
t 10488
 
0.2%
h 10488
 
0.2%
r 10488
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5128872
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1510660
29.5%
a 1038044
20.2%
l 1038044
20.2%
M 575916
 
11.2%
F 462128
 
9.0%
m 462128
 
9.0%
O 10488
 
0.2%
t 10488
 
0.2%
h 10488
 
0.2%
r 10488
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5128872
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1510660
29.5%
a 1038044
20.2%
l 1038044
20.2%
M 575916
 
11.2%
F 462128
 
9.0%
m 462128
 
9.0%
O 10488
 
0.2%
t 10488
 
0.2%
h 10488
 
0.2%
r 10488
 
0.2%

State/UT
Categorical

Distinct36
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.9 MiB
Gujarat
194907 
Maharashtra
110270 
Uttar Pradesh
99997 
Rajasthan
85271 
Karnataka
60163 
Other values (31)
497924 

Length

Max length40
Median length17
Mean length9.8984638
Min length3

Characters and Unicode

Total characters10378856
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHaryana
2nd rowGujarat
3rd rowMaharashtra
4th rowPunjab
5th rowRajasthan

Common Values

ValueCountFrequency (%)
Gujarat 194907
18.6%
Maharashtra 110270
 
10.5%
Uttar Pradesh 99997
 
9.5%
Rajasthan 85271
 
8.1%
Karnataka 60163
 
5.7%
Telangana 59527
 
5.7%
Andhra Pradesh 55542
 
5.3%
Madhya Pradesh 40175
 
3.8%
Tamil Nadu 34947
 
3.3%
Haryana 20455
 
2.0%
Other values (26) 287278
27.4%

Length

2025-03-26T08:01:17.529204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pradesh 212119
15.1%
gujarat 194907
13.9%
maharashtra 110270
 
7.9%
uttar 99997
 
7.1%
rajasthan 85271
 
6.1%
karnataka 60163
 
4.3%
telangana 59527
 
4.2%
andhra 55542
 
4.0%
and 41564
 
3.0%
madhya 40175
 
2.9%
Other values (37) 445001
31.7%

Most occurring characters

ValueCountFrequency (%)
a 2617117
25.2%
r 1049885
10.1%
h 824887
 
7.9%
t 724327
 
7.0%
n 506709
 
4.9%
s 502354
 
4.8%
d 498383
 
4.8%
e 362637
 
3.5%
356004
 
3.4%
u 319482
 
3.1%
Other values (33) 2617071
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10378856
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2617117
25.2%
r 1049885
10.1%
h 824887
 
7.9%
t 724327
 
7.0%
n 506709
 
4.9%
s 502354
 
4.8%
d 498383
 
4.8%
e 362637
 
3.5%
356004
 
3.4%
u 319482
 
3.1%
Other values (33) 2617071
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10378856
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2617117
25.2%
r 1049885
10.1%
h 824887
 
7.9%
t 724327
 
7.0%
n 506709
 
4.9%
s 502354
 
4.8%
d 498383
 
4.8%
e 362637
 
3.5%
356004
 
3.4%
u 319482
 
3.1%
Other values (33) 2617071
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10378856
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2617117
25.2%
r 1049885
10.1%
h 824887
 
7.9%
t 724327
 
7.0%
n 506709
 
4.9%
s 502354
 
4.8%
d 498383
 
4.8%
e 362637
 
3.5%
356004
 
3.4%
u 319482
 
3.1%
Other values (33) 2617071
25.2%
Distinct733
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-26T08:01:17.745796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.4189772
Min length3

Characters and Unicode

Total characters8827567
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPalwal
2nd rowMahisagar
3rd rowNandurbar
4th rowMuktsar
5th rowChittorgarh
ValueCountFrequency (%)
north 19463
 
1.6%
south 17961
 
1.5%
west 10896
 
0.9%
east 10740
 
0.9%
goa 10598
 
0.9%
mumbai 10486
 
0.9%
sikkim 10337
 
0.9%
chandigarh 10041
 
0.8%
kachchh 9990
 
0.8%
junagadh 9961
 
0.8%
Other values (736) 1094267
90.1%
2025-03-26T08:01:18.085320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1784582
20.2%
r 727252
 
8.2%
h 558297
 
6.3%
i 527466
 
6.0%
n 514690
 
5.8%
u 426224
 
4.8%
d 338586
 
3.8%
o 324132
 
3.7%
l 308603
 
3.5%
g 267658
 
3.0%
Other values (44) 3050077
34.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8827567
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1784582
20.2%
r 727252
 
8.2%
h 558297
 
6.3%
i 527466
 
6.0%
n 514690
 
5.8%
u 426224
 
4.8%
d 338586
 
3.8%
o 324132
 
3.7%
l 308603
 
3.5%
g 267658
 
3.0%
Other values (44) 3050077
34.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8827567
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1784582
20.2%
r 727252
 
8.2%
h 558297
 
6.3%
i 527466
 
6.0%
n 514690
 
5.8%
u 426224
 
4.8%
d 338586
 
3.8%
o 324132
 
3.7%
l 308603
 
3.5%
g 267658
 
3.0%
Other values (44) 3050077
34.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8827567
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1784582
20.2%
r 727252
 
8.2%
h 558297
 
6.3%
i 527466
 
6.0%
n 514690
 
5.8%
u 426224
 
4.8%
d 338586
 
3.8%
o 324132
 
3.7%
l 308603
 
3.5%
g 267658
 
3.0%
Other values (44) 3050077
34.6%
Distinct56
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.6 MiB
2025-03-26T08:01:18.285142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length69
Median length58
Mean length47.61037
Min length10

Characters and Unicode

Total characters49920997
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDakshin Haryana Bijli Vitran Nigam (DHBVN)
2nd rowMadhya Gujarat Vij Company Limited (MGVCL), Vadodara
3rd rowAdani Electricity Mumbai Limited
4th rowPunjab State Power Corporation Limited (PSPCL)
5th rowAjmer Vidyut Vitran Nigam Ltd
ValueCountFrequency (%)
limited 702349
 
11.0%
company 443394
 
6.9%
power 323410
 
5.1%
corporation 250310
 
3.9%
distribution 222808
 
3.5%
electricity 196895
 
3.1%
of 183746
 
2.9%
vidyut 170600
 
2.7%
nigam 150880
 
2.4%
vij 150554
 
2.4%
Other values (125) 3597784
56.3%
2025-03-26T08:01:18.638114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5344198
 
10.7%
i 4259986
 
8.5%
a 3955232
 
7.9%
t 3305382
 
6.6%
r 3055073
 
6.1%
o 2638936
 
5.3%
n 2276457
 
4.6%
e 2269322
 
4.5%
d 1817908
 
3.6%
m 1717496
 
3.4%
Other values (41) 19281007
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49920997
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5344198
 
10.7%
i 4259986
 
8.5%
a 3955232
 
7.9%
t 3305382
 
6.6%
r 3055073
 
6.1%
o 2638936
 
5.3%
n 2276457
 
4.6%
e 2269322
 
4.5%
d 1817908
 
3.6%
m 1717496
 
3.4%
Other values (41) 19281007
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49920997
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5344198
 
10.7%
i 4259986
 
8.5%
a 3955232
 
7.9%
t 3305382
 
6.6%
r 3055073
 
6.1%
o 2638936
 
5.3%
n 2276457
 
4.6%
e 2269322
 
4.5%
d 1817908
 
3.6%
m 1717496
 
3.4%
Other values (41) 19281007
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49920997
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5344198
 
10.7%
i 4259986
 
8.5%
a 3955232
 
7.9%
t 3305382
 
6.6%
r 3055073
 
6.1%
o 2638936
 
5.3%
n 2276457
 
4.6%
e 2269322
 
4.5%
d 1817908
 
3.6%
m 1717496
 
3.4%
Other values (41) 19281007
38.6%
Distinct366
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.0 MiB
Minimum2024-01-01 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-26T08:01:18.729038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-26T08:01:18.845905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
Rejected
736777 
Accepted
311755 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8388256
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccepted
2nd rowRejected
3rd rowRejected
4th rowAccepted
5th rowRejected

Common Values

ValueCountFrequency (%)
Rejected 736777
70.3%
Accepted 311755
29.7%

Length

2025-03-26T08:01:18.949132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T08:01:19.011684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
rejected 736777
70.3%
accepted 311755
29.7%

Most occurring characters

ValueCountFrequency (%)
e 2833841
33.8%
c 1360287
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736777
 
8.8%
R 736777
 
8.8%
A 311755
 
3.7%
p 311755
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2833841
33.8%
c 1360287
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736777
 
8.8%
R 736777
 
8.8%
A 311755
 
3.7%
p 311755
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2833841
33.8%
c 1360287
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736777
 
8.8%
R 736777
 
8.8%
A 311755
 
3.7%
p 311755
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2833841
33.8%
c 1360287
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736777
 
8.8%
R 736777
 
8.8%
A 311755
 
3.7%
p 311755
 
3.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
3 - 4 KW
734510 
4 - 5 KW
153863 
5 - 6 KW
77367 
2 - 3 KW
 
57957
Above 6 KW
 
20907

Length

Max length10
Median length8
Mean length8.0398786
Min length8

Characters and Unicode

Total characters8430070
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5 - 6 KW
2nd rowAbove 6 KW
3rd row3 - 4 KW
4th row5 - 6 KW
5th row3 - 4 KW

Common Values

ValueCountFrequency (%)
3 - 4 KW 734510
70.1%
4 - 5 KW 153863
 
14.7%
5 - 6 KW 77367
 
7.4%
2 - 3 KW 57957
 
5.5%
Above 6 KW 20907
 
2.0%
1 - 2 KW 3928
 
0.4%

Length

2025-03-26T08:01:19.090310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T08:01:19.166330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
kw 1048532
25.1%
1027625
24.6%
4 888373
21.3%
3 792467
19.0%
5 231230
 
5.5%
6 98274
 
2.4%
2 61885
 
1.5%
above 20907
 
0.5%
1 3928
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3124689
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027625
 
12.2%
4 888373
 
10.5%
3 792467
 
9.4%
5 231230
 
2.7%
6 98274
 
1.2%
2 61885
 
0.7%
A 20907
 
0.2%
Other values (5) 87556
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8430070
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3124689
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027625
 
12.2%
4 888373
 
10.5%
3 792467
 
9.4%
5 231230
 
2.7%
6 98274
 
1.2%
2 61885
 
0.7%
A 20907
 
0.2%
Other values (5) 87556
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8430070
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3124689
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027625
 
12.2%
4 888373
 
10.5%
3 792467
 
9.4%
5 231230
 
2.7%
6 98274
 
1.2%
2 61885
 
0.7%
A 20907
 
0.2%
Other values (5) 87556
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8430070
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3124689
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027625
 
12.2%
4 888373
 
10.5%
3 792467
 
9.4%
5 231230
 
2.7%
6 98274
 
1.2%
2 61885
 
0.7%
A 20907
 
0.2%
Other values (5) 87556
 
1.0%

Application Number
Real number (ℝ)

Unique 

Distinct1048532
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55013881
Minimum10000040
Maximum99999969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 MiB
2025-03-26T08:01:19.260532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10000040
5-th percentile14511760
Q132527885
median55017202
Q377516610
95-th percentile95466975
Maximum99999969
Range89999929
Interquartile range (IQR)44988725

Descriptive statistics

Standard deviation25961716
Coefficient of variation (CV)0.47191211
Kurtosis-1.198231
Mean55013881
Median Absolute Deviation (MAD)22495100
Skewness-0.0010991847
Sum5.7683814 × 1013
Variance6.7401071 × 1014
MonotonicityNot monotonic
2025-03-26T08:01:19.370347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89752584 1
 
< 0.1%
40086875 1
 
< 0.1%
65687203 1
 
< 0.1%
26535425 1
 
< 0.1%
33476001 1
 
< 0.1%
76127626 1
 
< 0.1%
82871642 1
 
< 0.1%
98597479 1
 
< 0.1%
62503643 1
 
< 0.1%
66204006 1
 
< 0.1%
Other values (1048522) 1048522
> 99.9%
ValueCountFrequency (%)
10000040 1
< 0.1%
10000049 1
< 0.1%
10000093 1
< 0.1%
10000308 1
< 0.1%
10000359 1
< 0.1%
10000489 1
< 0.1%
10000498 1
< 0.1%
10000570 1
< 0.1%
10000608 1
< 0.1%
10000635 1
< 0.1%
ValueCountFrequency (%)
99999969 1
< 0.1%
99999784 1
< 0.1%
99999773 1
< 0.1%
99999768 1
< 0.1%
99999652 1
< 0.1%
99999642 1
< 0.1%
99999572 1
< 0.1%
99999554 1
< 0.1%
99999399 1
< 0.1%
99999284 1
< 0.1%
Distinct379
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-26T08:01:19.574539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5946504
Min length8

Characters and Unicode

Total characters9011766
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-15
2nd rowDeclined
3rd rowDeclined
4th row2024-06-16
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
2024-07-29 1562
 
0.1%
2024-08-01 1542
 
0.1%
2024-07-30 1534
 
0.1%
2024-07-17 1530
 
0.1%
2024-07-27 1522
 
0.1%
2024-07-20 1520
 
0.1%
2024-08-03 1515
 
0.1%
2024-07-31 1509
 
0.1%
2024-07-18 1506
 
0.1%
Other values (369) 298015
28.4%
2025-03-26T08:01:19.949745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1473554
16.4%
2 800508
8.9%
D 736777
8.2%
c 736777
8.2%
i 736777
8.2%
l 736777
8.2%
n 736777
8.2%
d 736777
8.2%
0 680323
7.5%
- 623510
6.9%
Other values (8) 1013209
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9011766
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1473554
16.4%
2 800508
8.9%
D 736777
8.2%
c 736777
8.2%
i 736777
8.2%
l 736777
8.2%
n 736777
8.2%
d 736777
8.2%
0 680323
7.5%
- 623510
6.9%
Other values (8) 1013209
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9011766
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1473554
16.4%
2 800508
8.9%
D 736777
8.2%
c 736777
8.2%
i 736777
8.2%
l 736777
8.2%
n 736777
8.2%
d 736777
8.2%
0 680323
7.5%
- 623510
6.9%
Other values (8) 1013209
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9011766
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1473554
16.4%
2 800508
8.9%
D 736777
8.2%
c 736777
8.2%
i 736777
8.2%
l 736777
8.2%
n 736777
8.2%
d 736777
8.2%
0 680323
7.5%
- 623510
6.9%
Other values (8) 1013209
11.2%
Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 MiB
SkyPower Solar
82980 
BrightSun Power
78394 
GreenSpark Solar
74856 
RadiantSun Energy
74350 
SunWave Energy
70156 
Other values (15)
667796 

Length

Max length27
Median length23
Mean length18.872582
Min length13

Characters and Unicode

Total characters19788506
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSolarCrest Enterprises
2nd rowRadiantSun Energy
3rd rowGreenSpark Solar
4th rowGreenEnergy Systems
5th rowSolarHarvest Energy

Common Values

ValueCountFrequency (%)
SkyPower Solar 82980
 
7.9%
BrightSun Power 78394
 
7.5%
GreenSpark Solar 74856
 
7.1%
RadiantSun Energy 74350
 
7.1%
SunWave Energy 70156
 
6.7%
SunTech Solar Solutions 65409
 
6.2%
SunRise Renewable Solutions 60949
 
5.8%
SolarHarvest Energy 56934
 
5.4%
SolarPeak Innovations 56672
 
5.4%
InfiniteLight Solar 52436
 
5.0%
Other values (10) 375396
35.8%

Length

2025-03-26T08:01:20.059632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
solar 341181
 
14.9%
energy 231989
 
10.1%
solutions 156907
 
6.8%
power 117864
 
5.1%
systems 104880
 
4.6%
technologies 95493
 
4.2%
skypower 82980
 
3.6%
enterprises 78788
 
3.4%
brightsun 78394
 
3.4%
greenspark 74856
 
3.3%
Other values (19) 929923
40.6%

Most occurring characters

ValueCountFrequency (%)
e 2009512
 
10.2%
n 1738153
 
8.8%
r 1675411
 
8.5%
o 1548694
 
7.8%
S 1489587
 
7.5%
1244723
 
6.3%
a 1197891
 
6.1%
l 1003863
 
5.1%
t 842938
 
4.3%
s 838037
 
4.2%
Other values (26) 6199697
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19788506
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2009512
 
10.2%
n 1738153
 
8.8%
r 1675411
 
8.5%
o 1548694
 
7.8%
S 1489587
 
7.5%
1244723
 
6.3%
a 1197891
 
6.1%
l 1003863
 
5.1%
t 842938
 
4.3%
s 838037
 
4.2%
Other values (26) 6199697
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19788506
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2009512
 
10.2%
n 1738153
 
8.8%
r 1675411
 
8.5%
o 1548694
 
7.8%
S 1489587
 
7.5%
1244723
 
6.3%
a 1197891
 
6.1%
l 1003863
 
5.1%
t 842938
 
4.3%
s 838037
 
4.2%
Other values (26) 6199697
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19788506
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2009512
 
10.2%
n 1738153
 
8.8%
r 1675411
 
8.5%
o 1548694
 
7.8%
S 1489587
 
7.5%
1244723
 
6.3%
a 1197891
 
6.1%
l 1003863
 
5.1%
t 842938
 
4.3%
s 838037
 
4.2%
Other values (26) 6199697
31.3%
Distinct360
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-26T08:01:20.276196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5453844
Min length7

Characters and Unicode

Total characters8960109
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-26
2nd rowDeclined
3rd rowDeclined
4th row2024-06-21
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 17219
 
1.6%
2024-08-05 1564
 
0.1%
2024-08-10 1528
 
0.1%
2024-08-06 1521
 
0.1%
2024-07-31 1521
 
0.1%
2024-08-11 1520
 
0.1%
2024-08-02 1476
 
0.1%
2024-07-30 1473
 
0.1%
2024-07-28 1471
 
0.1%
Other values (350) 282462
 
26.9%
2025-03-26T08:01:20.590160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1490773
16.6%
n 771215
8.6%
2 763161
8.5%
d 753996
8.4%
i 753996
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 635656
7.1%
- 589072
 
6.6%
Other values (10) 991909
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8960109
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1490773
16.6%
n 771215
8.6%
2 763161
8.5%
d 753996
8.4%
i 753996
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 635656
7.1%
- 589072
 
6.6%
Other values (10) 991909
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8960109
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1490773
16.6%
n 771215
8.6%
2 763161
8.5%
d 753996
8.4%
i 753996
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 635656
7.1%
- 589072
 
6.6%
Other values (10) 991909
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8960109
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1490773
16.6%
n 771215
8.6%
2 763161
8.5%
d 753996
8.4%
i 753996
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 635656
7.1%
- 589072
 
6.6%
Other values (10) 991909
11.1%
Distinct358
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-26T08:01:20.807378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5335564
Min length7

Characters and Unicode

Total characters8947707
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2024-11-28
2nd rowDeclined
3rd rowDeclined
4th row2024-06-28
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 21353
 
2.0%
2024-08-09 1539
 
0.1%
2024-08-12 1523
 
0.1%
2024-08-16 1515
 
0.1%
2024-08-13 1509
 
0.1%
2024-08-07 1509
 
0.1%
2024-08-02 1493
 
0.1%
2024-08-08 1481
 
0.1%
2024-08-11 1481
 
0.1%
Other values (348) 278352
 
26.5%
2025-03-26T08:01:21.131768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1494907
16.7%
n 779483
8.7%
i 758130
8.5%
d 758130
8.5%
2 753095
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 626877
7.0%
- 580804
 
6.5%
Other values (10) 985950
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8947707
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1494907
16.7%
n 779483
8.7%
i 758130
8.5%
d 758130
8.5%
2 753095
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 626877
7.0%
- 580804
 
6.5%
Other values (10) 985950
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8947707
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1494907
16.7%
n 779483
8.7%
i 758130
8.5%
d 758130
8.5%
2 753095
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 626877
7.0%
- 580804
 
6.5%
Other values (10) 985950
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8947707
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1494907
16.7%
n 779483
8.7%
i 758130
8.5%
d 758130
8.5%
2 753095
8.4%
l 736777
8.2%
D 736777
8.2%
c 736777
8.2%
0 626877
7.0%
- 580804
 
6.5%
Other values (10) 985950
11.0%
Distinct344
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-26T08:01:21.339134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4037807
Min length7

Characters and Unicode

Total characters8811633
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-09
2nd rowDeclined
3rd rowDeclined
4th row2024-07-24
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 66711
 
6.4%
2024-09-05 1437
 
0.1%
2024-08-29 1402
 
0.1%
2024-09-10 1386
 
0.1%
2024-09-04 1373
 
0.1%
2024-09-07 1368
 
0.1%
2024-09-01 1364
 
0.1%
2024-09-06 1361
 
0.1%
2024-08-30 1352
 
0.1%
Other values (334) 234001
 
22.3%
2025-03-26T08:01:21.647568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1540265
17.5%
n 870199
9.9%
i 803488
9.1%
d 803488
9.1%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 617903
7.0%
0 540891
 
6.1%
- 490088
 
5.6%
Other values (10) 934980
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8811633
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1540265
17.5%
n 870199
9.9%
i 803488
9.1%
d 803488
9.1%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 617903
7.0%
0 540891
 
6.1%
- 490088
 
5.6%
Other values (10) 934980
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8811633
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1540265
17.5%
n 870199
9.9%
i 803488
9.1%
d 803488
9.1%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 617903
7.0%
0 540891
 
6.1%
- 490088
 
5.6%
Other values (10) 934980
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8811633
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1540265
17.5%
n 870199
9.9%
i 803488
9.1%
d 803488
9.1%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 617903
7.0%
0 540891
 
6.1%
- 490088
 
5.6%
Other values (10) 934980
10.6%
Distinct337
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-26T08:01:21.853844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3888427
Min length7

Characters and Unicode

Total characters8795970
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2024-12-17
2nd rowDeclined
3rd rowDeclined
4th row2024-07-31
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 71932
 
6.9%
2024-09-11 1404
 
0.1%
2024-09-16 1378
 
0.1%
2024-09-19 1375
 
0.1%
2024-09-10 1367
 
0.1%
2024-09-13 1365
 
0.1%
2024-09-21 1360
 
0.1%
2024-09-08 1359
 
0.1%
2024-09-12 1352
 
0.1%
Other values (327) 228863
 
21.8%
2025-03-26T08:01:22.151994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1545486
17.6%
n 880641
10.0%
i 808709
9.2%
d 808709
9.2%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 606686
 
6.9%
0 524839
 
6.0%
- 479646
 
5.5%
Other values (10) 930923
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8795970
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1545486
17.6%
n 880641
10.0%
i 808709
9.2%
d 808709
9.2%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 606686
 
6.9%
0 524839
 
6.0%
- 479646
 
5.5%
Other values (10) 930923
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8795970
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1545486
17.6%
n 880641
10.0%
i 808709
9.2%
d 808709
9.2%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 606686
 
6.9%
0 524839
 
6.0%
- 479646
 
5.5%
Other values (10) 930923
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8795970
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1545486
17.6%
n 880641
10.0%
i 808709
9.2%
d 808709
9.2%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 606686
 
6.9%
0 524839
 
6.0%
- 479646
 
5.5%
Other values (10) 930923
10.6%
Distinct331
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-26T08:01:22.354824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3775297
Min length7

Characters and Unicode

Total characters8784108
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2024-12-20
2nd rowDeclined
3rd rowDeclined
4th row2024-08-04
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 75886
 
7.2%
2024-09-24 1418
 
0.1%
2024-09-15 1393
 
0.1%
2024-09-27 1392
 
0.1%
2024-09-18 1379
 
0.1%
2024-09-13 1373
 
0.1%
2024-09-20 1355
 
0.1%
2024-10-01 1355
 
0.1%
2024-09-26 1344
 
0.1%
Other values (321) 224860
 
21.4%
2025-03-26T08:01:22.652905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1549440
17.6%
n 888549
10.1%
i 812663
9.3%
d 812663
9.3%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 597461
 
6.8%
0 513627
 
5.8%
- 471738
 
5.4%
Other values (10) 927636
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8784108
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1549440
17.6%
n 888549
10.1%
i 812663
9.3%
d 812663
9.3%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 597461
 
6.8%
0 513627
 
5.8%
- 471738
 
5.4%
Other values (10) 927636
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8784108
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1549440
17.6%
n 888549
10.1%
i 812663
9.3%
d 812663
9.3%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 597461
 
6.8%
0 513627
 
5.8%
- 471738
 
5.4%
Other values (10) 927636
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8784108
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1549440
17.6%
n 888549
10.1%
i 812663
9.3%
d 812663
9.3%
l 736777
8.4%
c 736777
8.4%
D 736777
8.4%
2 597461
 
6.8%
0 513627
 
5.8%
- 471738
 
5.4%
Other values (10) 927636
10.6%
Distinct315
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.3 MiB
2025-03-26T08:01:22.870634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.257994
Min length7

Characters and Unicode

Total characters8658771
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowPending
2nd rowDeclined
3rd rowDeclined
4th row2024-09-20
5th rowDeclined
ValueCountFrequency (%)
declined 736777
70.3%
pending 117665
 
11.2%
2024-10-24 1217
 
0.1%
2024-10-28 1205
 
0.1%
2024-10-19 1195
 
0.1%
2024-10-27 1190
 
0.1%
2024-10-26 1189
 
0.1%
2024-10-17 1175
 
0.1%
2024-10-10 1174
 
0.1%
2024-10-22 1161
 
0.1%
Other values (305) 184584
 
17.6%
2025-03-26T08:01:23.182096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1591219
18.4%
n 972107
11.2%
i 854442
9.9%
d 854442
9.9%
l 736777
8.5%
c 736777
8.5%
D 736777
8.5%
2 492755
 
5.7%
0 411046
 
4.7%
- 388180
 
4.5%
Other values (10) 884249
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8658771
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972107
11.2%
i 854442
9.9%
d 854442
9.9%
l 736777
8.5%
c 736777
8.5%
D 736777
8.5%
2 492755
 
5.7%
0 411046
 
4.7%
- 388180
 
4.5%
Other values (10) 884249
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8658771
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972107
11.2%
i 854442
9.9%
d 854442
9.9%
l 736777
8.5%
c 736777
8.5%
D 736777
8.5%
2 492755
 
5.7%
0 411046
 
4.7%
- 388180
 
4.5%
Other values (10) 884249
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8658771
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972107
11.2%
i 854442
9.9%
d 854442
9.9%
l 736777
8.5%
c 736777
8.5%
D 736777
8.5%
2 492755
 
5.7%
0 411046
 
4.7%
- 388180
 
4.5%
Other values (10) 884249
10.2%

Interactions

2025-03-26T08:01:13.199021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-26T08:01:23.254151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Acceptance StatusApplication NumberGenderProduction Capacity (KW)State/UTVendor Organization
Acceptance Status1.0000.0010.0000.0000.1160.000
Application Number0.0011.0000.0000.0010.0020.000
Gender0.0000.0001.0000.0010.0020.001
Production Capacity (KW)0.0000.0010.0011.0000.0000.001
State/UT0.1160.0020.0020.0001.0000.000
Vendor Organization0.0000.0000.0010.0010.0001.000

Missing values

2025-03-26T08:01:13.808650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-26T08:01:15.012675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
0FemaleHaryanaPalwalDakshin Haryana Bijli Vitran Nigam (DHBVN)2024-11-03Accepted5 - 6 KW400868752024-11-15SolarCrest Enterprises2024-11-262024-11-282024-12-092024-12-172024-12-20Pending
1FemaleGujaratMahisagarMadhya Gujarat Vij Company Limited (MGVCL), Vadodara2024-02-08RejectedAbove 6 KW65687203DeclinedRadiantSun EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
2MaleMaharashtraNandurbarAdani Electricity Mumbai Limited2024-12-15Rejected3 - 4 KW26535425DeclinedGreenSpark SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
3MalePunjabMuktsarPunjab State Power Corporation Limited (PSPCL)2024-06-06Accepted5 - 6 KW883089042024-06-16GreenEnergy Systems2024-06-212024-06-282024-07-242024-07-312024-08-042024-09-20
4MaleRajasthanChittorgarhAjmer Vidyut Vitran Nigam Ltd2024-08-31Rejected3 - 4 KW36219547DeclinedSolarHarvest EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
5FemaleDadra and Nagar Haveli and Daman and DiuDamanPowerGrid Corporation of India2024-09-21Accepted5 - 6 KW814240392024-09-25EcoSolar Enterprises2024-09-302024-10-052024-11-052024-11-112024-11-172024-12-06
6MaleRajasthanJhunjhunuAjmer Vidyut Vitran Nigam Ltd2024-04-07Rejected3 - 4 KW10653263DeclinedEcoSolar EnterprisesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
7FemaleAndhra PradeshAnantapurAndhra Pradesh Central Power Distribution Company Limited2024-08-04Rejected3 - 4 KW15267262DeclinedSunRise Renewable SolutionsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
8MaleTamil NaduDharmapuriTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-03-09Rejected3 - 4 KW73589792DeclinedBrightSun PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
9MaleRajasthanKotaJodhpur Vidyut Vitran Nigam Limited (JdVVNL)2024-09-24Accepted3 - 4 KW495919192024-10-09EcoSolar Enterprises2024-10-172024-10-212024-11-102024-11-162024-11-25Pending
GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
1048522FemaleRajasthanJodhpurAjmer Vidyut Vitran Nigam Ltd2024-04-02Rejected3 - 4 KW90881747DeclinedPowerSun TechnologiesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048523MaleMadhya PradeshHardaMadhya Pradesh Madhya Kshetra Vidyut Vitaran Company Limited2024-05-29Rejected5 - 6 KW27545400DeclinedSunTech Solar SolutionsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048524FemaleGujaratGir SomnathPaschim Gujarat Vij Company Limited (PGVCL), Rajkot2024-07-30Accepted1 - 2 KW364642782024-08-11SolarPeak Innovations2024-08-242024-08-262024-09-122024-09-212024-09-282024-11-04
1048525MaleUttar PradeshLalitpurLucknow Electricity Supply Administration (LESA), Lucknow City2024-09-17Rejected3 - 4 KW98547821DeclinedEcoSolar EnterprisesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048526MaleAndhra PradeshVizianagaramAndhra Pradesh Central Power Distribution Company Limited2024-08-14Rejected3 - 4 KW75198985DeclinedPowerSun TechnologiesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048527FemaleTamil NaduTiruvannamalaiTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-07-18Rejected4 - 5 KW95765516DeclinedEcoSolar EnterprisesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048528MaleSikkimNorth SikkimPowerGrid Corporation of India2024-03-02Accepted3 - 4 KW219328282024-03-07InfiniteLight Solar2024-03-172024-03-192024-04-182024-04-262024-05-012024-06-21
1048529MaleAndhra PradeshKrishnaAndhra Pradesh Central Power Distribution Company Limited2024-10-12Rejected3 - 4 KW78480366DeclinedSolarPeak InnovationsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048530MaleRajasthanJaipurAjmer Vidyut Vitran Nigam Ltd2024-09-23Rejected3 - 4 KW66402372DeclinedSolarHarvest EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048531MaleTelanganaWanaparthySouthern Power Distribution Company of Telangana Limited (TSSPDCL)2024-07-26Rejected3 - 4 KW89752584DeclinedSunWave EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined